Formal modeling in psychology

Buridan’s Ass

Felix Schönbrodt

felix.schoenbrodt@psy.lmu.de

Ludwig-Maximilians-Universität München

2023-09-19

A theory crisis in psychology?

The relation of data and phenomena

%%{ init: { 'flowchart': { 'curve': 'natural' } } }%%
flowchart LR
  T(Theory)
  P(Phenomena)
  D(Data)
  
  T -- "Explanation" --> P
  P -- "Abduction" --> T
  P -- "Prediction" --> D
  D -- "Generalization" --> P

The relation of data and phenomena

%%{ init: { 'flowchart': { 'curve': 'natural' } } }%%
flowchart LR
  P(Phenomena)
  D(Data)
  
  P -- "Prediction" --> D
  D -- "Generalization" --> P

Phenomena: Stable and general features of the world in need of explanation. Can be understood as robust generalizations of patterns in empirical data. They are the explanatory targets for scientific theories. In psychology often called “effects” or “findings”.

Data: Relatively direct observations. Refer to particular empirical patterns in concrete data sets rather than empirical generalizations (which would be phenomenona).

The relation of data and phenomena

Generalization

%%{ init: { 'flowchart': { 'curve': 'natural' } } }%%
flowchart LR
  P(Phenomena)
  D(Data)
  
  P -- "Prediction" --> D
  D -- "Generalization" --> P
  
  linkStyle 1 stroke-width:2px,stroke:red,color:red;

Data provide evidence for the existence of empirical phenomena: You generalize from one or more data sets with strong evidence to a general phenomenon.

Generalize to what? UTOS framework:

Units (i.e., sample characteristics): To which other types of tested units does it generalize?
Treatments: Does it generalize to other operationalizations of the independent variable/treatment?
Outcomes: Does it generalize to other operationalizations of the dependent variable/outcome?
Settings: Does it generalize to other settings, e.g. lab vs. field, other countries?

To claim a (robust) phenomenon, you ideally need:

Independent replications of specific operationalizations (U, maybe S)
Conceptual replications with different operationalizations (UTOS).

The relation of data and phenomena 3

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flowchart LR
  P(Phenomena)
  D(Data)
  
  P -- "Prediction" --> D
  D -- "Generalization" --> P
  
  linkStyle 1 stroke-width:2px,stroke:red,color:red;

Probably most of psychology is about establishing phenomena (disguised as “theories”).

Techniques used to detect data patterns:

Factor analysis
Principal components analysis
Regression
ANOVA
…

The relation of data and phenomena

Prediction

%%{ init: { 'flowchart': { 'curve': 'natural' } } }%%
flowchart LR
  P(Phenomena)
  D(Data)
  
  P -- "Prediction" --> D
  D -- "Generalization" --> P
  
  linkStyle 0 stroke-width:2px,stroke:red,color:red;

Phenomena (once their existence has been established) predict similar data patterns in new data sets of the same operationalization (as in “direct replication”) and ideally also for new operationalizations (as in “conceptual replication”, changing more UTOS dimensions).

Interlude: The risky shift phenomenon 1

The risky shift phenomenon: A group’s decisions are riskier than the average of the individual decisions of members before the group met (i.e., the group discussion made individuals riskier).

Area of very active research in social psychology in the 1960s.
“It could be easily replicated. Most of the replication studies […] employed the CDQ [Choice Dilemma Questionnaire] as their stimulus set, and they generally had no trouble obtaining the basic risky shift result.”
Today we know that there is no risky shift. “It is now clear that the items contained in the original CDQ are in no sense a representative sample of the universe of all possible items. Instruments similar to the CDQ could readily be constructed whose scores would display risky shifts, cautious ones, or none at all” (Cartwright, 1971, p. 368).
In the early risky shift literature, theoretical progress was unnecessarily impeded by multiple generations of replication studies (k ⋍ 200), nearly all relying on the same CQD questionnaire.

Interlude: The risky shift phenomenon 2

Questions for discussion (10 min.):

Analyse the situation in the UTOS dimensions (units, treatments, outcomes, settings): To which dimensions did the successful replications (not) refer to?
Is the “risky shift” finding - as demonstrated in the early publications - a phenomenon?

My take: It is a phenomenon (though a weak one), as it generalizes to new units (i.e., data sets) of the same operationalization. But the generalizability was much weaker than initially expected. It is a phenomenon of this specific stimulus set (treatment operationalization) and suggests certain types of research questions (e.g., “What is so specific to this stimulus set?”).

Replication crisis

Focus on phenomena

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flowchart LR
  P(Phenomena)
  D(Data)
  
  P -- "Prediction" --> D
  D -- "Generalization" --> P

The concerns of the replication crisis typically referred to the relation between data and phenomena:

Does an empirical pattern even exist? (Or is it a false positive?)
If we found a reproducible pattern with a specific operationalization: Is it generalizable (to other measures, other cultural contexts, other samples)?
Do we even have a phenomenon in a particular research line? And how strongly should I belief in the existence of a phenomenon, given the empirical evidence?

Replication crisis

Focus on phenomena

%%{ init: { 'flowchart': { 'curve': 'natural' } } }%%
flowchart LR
  T(Theory)
  P(?? Phenomena ??)
  D(Data)
  
  T -- "Explanation" --> P
  P -- "Abduction" --> T
  P ---> D
  D -. "?? Generalization ??" .-> P
  
  linkStyle 2 stroke-width:0px,stroke:grey,color:grey;
  linkStyle 3 stroke-width:2px,stroke:red,color:red;

Doubts about phenomena propagate to theories: If there is no phenomenon to explain, any explanatory theory gets obsolete.

From replication crisis to theory crisis

From replication crisis to theory crisis 1

“We argue that a further cause of poor replicability is the often weak logical link between theories and their empirical tests.”

From replication crisis to theory crisis 2

Obstacles to building useful theories in psychology:

relative lack of robust phenomena that impose constraints on possible theories
problems of validity of psychological constructs
obstacles to discovering causal relationships between psychological variables

Slide by Karolin Salmen, CC-BY

From replication crisis to theory crisis 3

Wenn die Psychologie das Fehlen eines theoretischen Fundaments beklagt, so greift diese Diagnose zu kurz: Woran es ihr eigentlich mangelt, ist ein Nährboden, auf dem ein solches Fundament überhaupt entstehen könnte. Ihr fehlt das große heuristische Narrativ. Die Physik hat ein solches Narrativ; es ist der Glaube an die Sphärenmusik einer kosmischen Harmonie, erkennbar an dem Vertrauen, mit dem man erwartet, auf Symmetrien, Erhaltungssätze und überhaupt auf einfache Zusammenhänge zu stoßen. Die Psychologen haben sich dieses Narrativ ausgeborgt; aber bei ihnen funktioniert es nicht.

Auch für sie aber läge ein solcher Kompass bereit, und die Systemtheorie könnte sie lehren, ihn zu nutzen. Den Technikern ist er seit je vertraut, und ebenso ordnet und lenkt er das Denken der Biologen […]. Dieses heuristische Narrativ - wir werden es in diesem Buch unter dem Stichwort des demiurgischen Prinzips kennenlernen - ist die Vision des kosmischen Ingenieurs, des Weltbaumeisters, der den Organismus unter der Leitidee nicht der Harmonie, sondern der Funktionalität, des “Wozu” konstruiert hat.

End

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